A daily-rebalanced, multi-model system that blends equity exposure with volatility and bond hedges. It uses momentum-ish signals and moving averages to decide when to buy or hedge (often via UVXY/SVXY and tech/benchmarks like SPY/QQQ), while sprinkling in bond ETFs and anti-beta funds to limit drawdowns. It’s designed to adapt to market regimes, not to just buy-and-hold.

- The system is built from many modules (groups). Each module has its own rules about when to buy, hold, or sell a given ETF. Think of the modules as separate decision-makers that compete for your cash, and the final allocation is a blended result of all active rules. - The biggest, most visible module is WM 74's Frontrunner, which uses signals based on momentum-like indicators and price relationships (for example, checks involving RSIs and moving averages of various ETFs). When a condition fires, it tends to allocate to volatility-related ETFs (UVXY, UVXY 2x), or to core market proxies (QQQ, SPY, VTI, XLK, etc.), depending on which rule is satisfied. - A cluster of hedge-oriented sub-strategies (DereckN Hedge System, TMF Momentum, SVXY FTLT, SVXY FTLT | V2, and the Shorting SPY group) moves money into hedges or currency-like bets (short volatility SVXY vs long volatility UVXY, U.S. Treasuries via TMF/TMV/SHV/SHY/TLT/IEF/BND, and select anti-beta funds like BTAL) to reduce downside risk when signals deteriorate. - There are top/bottom selector rules (filters) that choose a single best candidate (top 1 by cumulative return or moving-average criteria, etc.) for certain slices of the portfolio. When those rules fire, they can overweight or narrow to specific ETFs. - The portfolio mixes equity exposure with hedges and with targeted bond exposure to manage risk across regimes. Leveraged ETFs (e.g., TQQQ, TECL, UVXY, TMF 3x, TMV 3x) are used to amplify moves under certain conditions, which can boost both upside and downside. - The overall allocation aims to be 100/100 in the sense of balancing weights, but many blocks show cash allocations and conditional increments, so the final exposure varies day-to-day. Overall, the strategy attempts to ride momentum in equities during favorable regimes while switching to hedges (volatility, Treasuries, anti-beta funds) during risk-off regimes, with frequent rebalancing to keep the target risk footprint.

Regime-aware, multi-model strategy blending equities, volatility hedges, and bonds to diversify risk. Designed to cushion swings and provide downside protection as portfolio insurance; current OOS returns trail the S&P 500.